1. Field of the Invention
The present invention relates generally to computer-implemented expert rules for artificial intelligence programs. In particular, a computerized method for generating questions applicable for intelligent tutorials is disclosed. In the present embodiment, a list of question-generating rules is added to an intelligent tutoring system, and the applicability of each rule in the list is tested upon every action that changes the state of the tutoring session. Students then using the tutorial are presented a menu of applicable questions that may be asked about each step taken, and accordingly ask at least one of the generated questions and get an answer. An intelligent tutoring system that is adapted to be enhanced by the present invention is that such computerized tutorial disclosed in U.S. patent application Ser. No. 09/769,910, now U.S. Pat. No. 6,540,520, the entire disclosure of which is herein incorporated by reference.
2. Description of the Related Art
Current tutoring programs routinely limit the problems and or questions available to the student to a fixed preset list, which rules out, for example, the possibility of providing tutoring on the teacher's own assignments. Typically, in non-intelligent tutorial software, the student only selects answers in multiple-choice form, and is told whether the selection is right or wrong. Several programs present a worked-out solution for study, but this does nothing to address the student's own mistake and the reasons behind them.
This has led to criticism of scripted “linear” instructional approaches that are too rigid and inflexible to support meaningful learning. There is a real need for a further dimension of interactivity. Fortunately, the approach used for constructing meaningful explanations, which is described by U.S. Pat. No. 6,540,520, is now taught. There now exists the opportunity for answering other useful questions about problems and their solutions. A way to leverage the benefit of the reasoning process of an artificial intelligence expert system is by exporting it in the form of various questions the system can answer. This can permit the student to ask questions about the situation even before they are ready to attempt the problems. Therefore, there is a need for a question-generating mechanism to be implemented into an expert system framework, wherein a student can ask dynamic, context-dependent questions about the problem or situation.
By interactively answering a variety of detailed questions for the student at each step, or at least providing that option, the particular pedagogical approach of the tutor is specifically oriented to help beginning and lower-performing students the most, who often cannot make any start on a problem, or do not feel comfortable attempting to do so. The ability of the tutor to answer questions makes it possible for students to conduct exploratory inquiry even before they can attempt the problems. At each step, questions are displayed in a menu the student can choose from as needed, selecting as many or as few questions as desired. Many different paths of inquiry are possible for the same problem, with the student directing the inquiry. The questions and answers are highly targeted and context-specific, changing at each step, and model good scientific thinking about the problem domain and underlying concepts. This is very important in fostering the development of the student's own self-explanation and question-asking abilities.